Reconciling certification and intact forest landscape conservation

Author(s): Kleinschroth, F. Garcia, C. Ghazoul, J.
Publication Year: 2019
Publication Type: Journal Article
Source: Ambio (48, 153-159)
Code:
Access to the Study:
Permanent Resource Identifier: Open link
FSC Resource Identifier: Open link
Collections: FSC Research Portal
Abstract

In 2014, the Forest Stewardship Council (FSC) added a new criterion to its principles that requires protection of intact forest landscapes (IFLs). An IFL is an extensive area of forest that lacks roads and other signs of human activity as detected through remote sensing. In the Congo basin, our analysis of road networks in formally approved concessionary logging areas revealed greater loss of IFL in certified than in noncertified concessions. In areas of informal (i.e., nonregulated) extraction, road networks are known to be less detectable by remote sensing. Under the current definition of IFL, companies certified under FSC standards are likely to be penalized relative to the noncertified as well as the informal logging sector on account of their planned road networks, despite an otherwise better standard of forest management. This could ultimately undermine certification and its wider adoption, with implications for the future of sustainable forest management.

Summary
Description
Citation
Kleinschroth, F., Garcia, C. and Ghazoul, J., 2019. Reconciling certification and intact forest landscape conservation. Ambio, 48(2), pp.153-159.
Access Rights: Public, Open access
Certification Body:
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Name of the Company:
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Relevance for FSC Standard Developers:
Sustainability dimension(s): Economic Environmental
Topics: (not yet curated)
Subtopics: (not yet curated)
Subject Keywords: Forests Wildfires Protected areas
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Regions: Africa
Countries: Congo
Forest Zones: Tropical
Forest Type: Natural Forest
Tenure Ownership: (not yet curated)
Tenure Management: (not yet curated)
Evidence Category: FSC effect-related studies
Evidence Type: Comparative study with no matched control
Evidence Subtype: Data collected post-intervention
Data Type: Remote sensing